CLOSE
Original image

Why Do College Basketball Teams Cut Down the Nets?

Original image

© Wally McNamee/CORBIS

The men’s NCAA Division I hoops championship game is tonight, and we can’t tell you whether UConn or Butler is going to win. We can predict two things, though. The winning team will cut down the nets. And CBS will show a highlight montage set to the song “One Shining Moment.” Let’s take a look at the origins of these traditions.

Who’s responsible for college teams cutting down the nets after big wins?

North Carolina State coach Everett Case didn’t realize he was starting a trend in 1947. He just wanted a souvenir.

USA Today’s Michael Gluskin wrote a terrific piece on the origins of college hoops’ net-cutting tradition in 2005. According to Gluskin, Coach Case was so delighted with the Wolfpack’s Southern Conference title win that he decided to cut down the nets as souvenirs.

Of course, being a pioneer can be tough. Since Case was the first coach to cut down the nets, arena workers didn’t have a ladder at the ready for his big moment. Instead, his players had to hoist their coach onto their shoulders as he did his snipping.

Case might not have been the true inventor of the net-cutting tradition, though. While he deservedly gets credit for being the college coach who popularized the net-cutting ritual, some sources – including Tim Peeler’s Legends of N.C. State Basketball - claim Case actually brought the tradition with him from Indiana, where he’d been a hugely successful high school coach before coming to Raleigh to coach the Wolfpack. Either way, cutting down the nets may have remained an obscure Hoosier State tradition had Case not brought the practice to the national stage.

What about the other big postgame tradition, the tourney highlight montage set to “One Shining Moment”?

Glad you asked. Any hoops fan can tell you that the song is pretty cheesy and more than a little over-the-top. It’s also one of the best parts of CBS’ annual coverage of the Final Four. Where the heck did “One Shining Moment” come from, and why do we only hear it once a year?

To be fair, there are really only so many opportunities to play a slightly sappy song about basketball. Peter Hyman of The New York Times wrote a profile on David Barrett, the composer of the tune, in 2007. The song is actually the product of an ill-fated attempt to woo a woman.

In 1986, Barrett was an unknown 31-year-old folk singer when he went to a bar in East Lansing, MI, to watch a Boston Celtics game. When a beautiful waitress sat down next to him after her shift, Barrett decided to spark conversation by chatting about Larry Bird’s hoops abilities.

Believe it or not, the singer’s ploy didn’t work. Barrett told Hyman that he resolved to write a tune that could show the waitress who snubbed him just how beautiful basketball could be. The next morning he wrote the song on a napkin in 20 minutes.

The song might have faded into oblivion as one of the odder “I’ll show them all!” pipedreams a folk singer has ever had. Barrett had a well-placed buddy, though. Journalist Armen Keteyian had been a high school classmate of Barrett’s, and he passed a demo tape of the song around to network producers.

CBS liked the song and bought it for use in a highlight package it planned to air after Super Bowl XXI. (Yes, the iconic hoops song was very nearly a football song.) The package didn’t make the final cut when the broadcast ran long, but the network revived it following the 1987 Final Four.

The package with “One Shining Moment” was a huge hit, and CBS has kept it around ever since. Barrett provided the vocals for the original version of the song, but some big names have belted out the tune since. Teddy Pendergrass took over vocal duties for a few years in the 90s before Luther Vandross recorded his own version. Jennifer Hudson sang the song for last year’s championship package, but fans roundly criticized her version. (It’s worth noting, though, that fans were mostly irked that producers had inserted so many shots of Hudson in the highlight montage; nobody’s debating that Hudson’s a tremendous singer.)

Here's last year's version, which YouTube user sparty801 re-edited with Vandross' rendition of the song.

Original image
iStock // Ekaterina Minaeva
technology
arrow
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

Original image
iStock
Animals
arrow
Scientists Think They Know How Whales Got So Big
May 24, 2017
Original image
iStock

It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

SECTIONS
BIG QUESTIONS
BIG QUESTIONS
WEATHER WATCH
BE THE CHANGE
JOB SECRETS
QUIZZES
WORLD WAR 1
SMART SHOPPING
STONES, BONES, & WRECKS
#TBT
THE PRESIDENTS
WORDS
RETROBITUARIES